Alain Boucher

Cell Migration Analysis After In Vitro Wounding Injury with a Multi-Agent Approach

Artificial Intelligence Review, 1998

This paper presents a multiagent system for studying in vitro cell motion. A typical application ... more This paper presents a multiagent system for studying in vitro cell motion. A typical application on the wound closure process is presented to illustrate the possibilities of the system, where different image sequences will be treated. The motion issue involves three aspects: image segmentation, object tracking and motion analysis. The current system version focuses mainly on the image segmentation aspect. A general agent model has been designed, which will be further expanded to include tracking and motion analysis behaviors as well. The agents integrate three basic behaviors: perception, interaction and reproduction. The perception evaluates pixels upon static and motion-based criteria. The interaction behavior allows two agents to merge or to negotiate parts of regions. The negotiation can be seen as a segmentation refinement process done by the agents. Finally, the reproduction behavior defines an exploration strategy of the images. Agents can start other agents around them, or they can duplicate themselves in the next frame. The frames are processed in pipeline, where previous information is used to treat the current frame. One unique agent model exist. Agents are specialized on execution time according to their goals. The results, coming from an existing prototype, show different types of cell behavior during cell migration, based on cell nuclei analysis.

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Multimedia scenario extraction and content indexing for e-learning

In this paper, we present the use of multimodal content anal-ysis in the MARVEL (Multimodal Analy... more In this paper, we present the use of multimodal content anal-ysis in the MARVEL (Multimodal Analysis of Recorded Video for E-Learning) project. In this project, we record teachers giving their lectures in class and semi-automatically analyze the video-audio content in order to help transfer this lecture into a multimedia course for e-learning. We distin-guish two primary goals in this application: scenario extrac-tion (mostly from video) and content indexing (mostly from text and speech). Three objects take place in these goals: the teacher, the screen (for slide projection) and the white-board (for handwriting). These goals and the roles of all objects are explained in details, as well as our preliminary results. Through this application, we are giving some ideas about multimodality analysis and its formalization.

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artificial maieutic approach for eliciting experts'

SURVEILLANCE VIDEO INDEXING AND RETRIEVAL USING OBJECT FEATURES AND SEMANTIC EVENTS

International Journal of Pattern Recognition and Artificial Intelligence, 2009

In this paper, we propose an approach for surveillance video indexing and retrieval. The objectiv... more In this paper, we propose an approach for surveillance video indexing and retrieval. The objective of this approach is to answer five main challenges we have met in this domain: (1) the lack of means for finding data from the indexed databases, (2) the lack of approaches working at different abstraction levels, (3) imprecise indexing, (4) incomplete indexing, (5) the lack of user-centered search. We propose a new data model containing two main types of extracted video contents: physical objects and events. Based on this data model we present a new rich and flexible query language. This language works at different abstraction levels, provides both exact and approximate matching and takes into account users' interest. In order to work with the imprecise indexing, two new methods respectively for object representation and object matching are proposed. Videos from two projects which have been partially indexed are used to validate the proposed approach. We have analyzed both query language usage and retrieval results. The obtained retrieval results are analyzed by the average normalized ranks are promising. The retrieval results at the object level are compared with another state of the art approach.

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Image formation model of a 3D translucent object observed in light microscopy

Proceedings. International Conference on Image Processing, 2002

... The light dispersion is preponderant over the refraction, so it is *The authors would like to... more

Object recognition from 3D blurred images

Object recognition supported by user interaction for service robots, 2002

A multi-agent system to segment living cells

Proceedings of 13th International Conference on Pattern Recognition, 1996

This paper presents a multi-agent system for the segmentation of deformable moving objects. Our a... more This paper presents a multi-agent system for the segmentation of deformable moving objects. Our application concerns cell image sequences. The agents integrate three basic behaviors: segmentation, interaction and reproduction. The segmentation behavior is based on region growing methods. Pixels are evaluated upon static and motion-based criteria. The interaction behavior allows two agents to merge or to negotiate parts of regions.

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Cell Migration Analysis After In Vitro Wounding Injury with a Multi-Agent Approach

Artificial Intelligence for Biology and Agriculture, 1998

This paper presents a multiagent system for studying in vitro cell motion. A typical application ... more This paper presents a multiagent system for studying in vitro cell motion. A typical application on the wound closure process is presented to illustrate the possibilities of the system, where different image sequences will be treated. The motion issue involves three aspects: image segmentation, object tracking and motion analysis. The current system version focuses mainly on the image segmentation aspect. A general agent model has been designed, which will be further expanded to include tracking and motion analysis behaviors as well. The agents integrate three basic behaviors: perception, interaction and reproduction. The perception evaluates pixels upon static and motion-based criteria. The interaction behavior allows two agents to merge or to negotiate parts of regions. The negotiation can be seen as a segmentation refinement process done by the agents. Finally, the reproduction behavior defines an exploration strategy of the images. Agents can start other agents around them, or they can duplicate themselves in the next frame. The frames are processed in pipeline, where previous information is used to treat the current frame. One unique agent model exist. Agents are specialized on execution time according to their goals. The results, coming from an existing prototype, show different types of cell behavior during cell migration, based on cell nuclei analysis.

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Development of a semi-automatic system for pollen recognition

A semi-automatic system for pollen recognition is studied for the european project ASTHMA. The go... more A semi-automatic system for pollen recognition is studied for the european project ASTHMA. The goal of such a system is to provide accurate pollen concentration measurements. This information can be used as well by the palynologists, the clinicians or a forecast system to predict pollen dispersion. At first, our emphasis has been put on Cupressaceae, Olea, Poaceae and Urticaceae pollen types. The system is composed of two modules: pollen grain extraction and pollen grain recognition. In the first module, the pollen grains are observed in light microscopy and are extracted automatically from a pollen slide coloured with fuchsin and digitized in 3D. In the second module, the pollen grain is analyzed for recognition. To accomplish the recognition, it is necessary to work on 3D images and to use detailed palynological knowledge. This knowledge describes the pollen types according to their main visible characteristerics and to those which are important for recognition. Some pollen structures are identified like the pore with annulus in Poaceae, the reticulum in Olea and similar pollen types or the cytoplasm in Cupressaceae. The preliminary results show the recognition of some pollen types, like Urticaceae or Poaceae or some groups of pollen types, like reticulate group.

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Unsupervised and Interactive Semi-supervised Clustering for Large Image Database Indexing and Retrieval

by Alain Boucher and Muriel Visani

ABSTRACT The feature space structuring methods play a very important role in finding information ... more ABSTRACT The feature space structuring methods play a very important role in finding information in large image databases. They organize indexed images in order to facilitate, accelerate and improve the results of further retrieval. Clustering, one kind of feature space structuring, may organize the dataset into groups of similar objects without prior knowledge unsupervised clustering or with a limited amount of prior knowledge semi-supervised clustering. In this paper, we present both formal and experimental comparisons of different unsupervised clustering methods for structuring large image databases. We use different image databases of increasing sizes Wang, PascalVoc2006, Caltech101, Corel30k to study the scalability of the different approaches. Then, we present a new interactive semi-supervised clustering model, which allows users to provide feedback in order to improve the clustering results according to their wishes. Moreover,we also compare, experimentally, our proposed model with the semi-supervised HMRF-kmeans clustering method.

Trajectory-based video indexing and retrieval enabling relevance feedback

This paper is proposing an approach for retrieving videos based on object trajectories. First, a ... more This paper is proposing an approach for retrieving videos based on object trajectories. First, a trajectory is translated into a sequence of symbols based on a symbolic representation, beyond the initial numeric representation, which does not suffer from scaling, translation or rotation. Then, in order to compare trajectories based on their symbolic representations, two similarity measures are proposed, inspired by works in bioinformatic. Moreover, based on these similarity measures, two relevance feedback strategies are given. Experimental results for two databases show that the proposed similarity measures gave results as good as other existing measures. Real advantages of these measures are the possibility for the partial matching and for relevance feedback.

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A Pixel Labeling Framework for Comparing Texture Features: Application to Digitized Ancient Books

by Maroua Mehri and Alain Boucher

Interactive Learning of Independent Experts' Criteria for Rescue Simulations

Journal of Universal Computer Science, 2009

The goal of our work is building a DSS (Decision Support System) for resource allocation and plan... more The goal of our work is building a DSS (Decision Support System) for resource allocation and planning in the situations of natural disasters emergencies in urban areas such as Hanoi in Vietnam. A first step has been to conceive Multi-agent environment that supports simulation of disasters taking into account geospatial, temporal and rescue organizational information. The problem we address is the acquisition of situated expert knowledge that is used to organize rescue missions. We propose an approach based on participatory techniques, interactive learning and machine learning. This paper presents an algorithm that incrementally builds a model of the expert knowledge by online analysis of its interaction with the simulator's proposed scenario.

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Friends and Buffaloes

Technologies, Advances and New Discoveries, 2008

A texture-based pixel labeling approach for historical books

by Alain Boucher and Maroua Mehri

Pattern Analysis and Applications, 2015

Over the last few years, there has been tremendous growth in the automatic processing of digitize... more Over the last few years, there has been tremendous growth in the automatic processing of digitized historical documents. In fact, finding reliable systems for the interpretation of ancient documents has been a topic of major interest for many libraries and the prime issue of research in the document analysis community. One important challenge is to refine well-known approaches based on strong a priori knowledge (e.g. the document image content, layout, typography, font size and type, scanning resolution, image size, etc.). Nevertheless, a texture analysis approach has consistently been chosen to segment a page layout when information is lacking on document structure and content. Thus, in this article a framework is proposed to investigate the use of texture as a tool for automatically determining homogeneous regions in a digitized historical book and segmenting its contents by extracting and analyzing texture features independently of the layout of the pages. The proposed framework is parameter-free and applicable to a large variety of ancient of books. It does not assume a priori information regarding document image content and structure. It consists of two phases: a texture-based feature extraction step and unsupervised clustering and labeling task based on the consensus clustering, hierarchical ascendant classification, and nearest neighbor search algorithms. The novelty of this work lies in the clustering of extracted texture descriptors to find automatically homogeneous regions, i.e. graphic and textual regions, by using the clustering approach on an entire book instead of processing each page individually. Our framework has been evaluated on a large variety of historical books and achieved promising results.

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Clusters-Based Relevance Feedback for CBIR: A Combination of Query Movement and Query Expansion

2010 IEEE RIVF International Conference on Computing & Communication Technologies, Research, Innovation, and Vision for the Future (RIVF), 2010

This paper presents a cluster-based relevance feedback technique. Our method combines two popular... more This paper presents a cluster-based relevance feedback technique. Our method combines two popular techniques of relevance feedback: query point movement and query expansion. The query expansion gives better result than the query point movement but there is still a problem with the insufficiency and the overlap of relevant and irrelevant images. To enhance the efficiency in such cases, irrelevant images

Region-Based Semi-automatic Annotation Using the Bag of Words Representation of the Keywords

2009 Fifth International Conference on Image and Graphics, 2009

... segmentation methods for feature detection are used in [1] and [15 ... Interest points are be... more

Unsupervised and Semi-Supervised Clustering for Large Image Database Indexing and Retrieval

by Alain Boucher and Muriel Visani

2012 IEEE RIVF International Conference on Computing & Communication Technologies, Research, Innovation, and Vision for the Future, 2012

In recent years, the expansion of acquisition devices such as digital cameras, the evolution of s... more In recent years, the expansion of acquisition devices such as digital cameras, the evolution of storage and transmission techniques of multimedia documents and the developement of tablet computers facilitate the growing of many large image databases as well as the interactions with the users. This increases the need for efficient and robust methods for finding information in these huge masses of data, including feature extraction methods and feature space structuring methods. The feature extraction methods aim to extract feature descriptors for each image. The feature space structuring methods organize indexed images in order to facilitate, accelerate and improve the results of further retrieval. Clustering is one kind of feature space structuring. Clustering may organize the dataset into groups of similar objects without prior knowledge (unsupervised clustering) or with a limited amount of prior knowledge (semi-supervised clustering). In this article, we present both formal and experimental comparisons of different unsupervised clustering methods for structuring large image databases. We use different image databases of increasing sizes (Wang, PascalVoc2006, Caltech101, Corel30k) to study the scalability of the different approaches. Moreover, a summary of semi-supervised clustering methods is presented and an interactive semi-supervised clustering model using the HMRF-kmeans is experimented on the Wang image database in order to analyse the improvement of the clustering results when user feedbacks are provided.

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An Artificial Maieutic Approach for Eliciting Experts’ Knowledge in Multi-agent Simulations

Lecture Notes in Computer Science, 2006

Models of human behaviours used in multi-agent simulations are limited by the ability of introspe... more Models of human behaviours used in multi-agent simulations are limited by the ability of introspection of the social actors: some of their knowledge (reflexes, habits, non-formalized expertise) cannot be extracted through interviews. The use of computer-mediated role playing games put these actors into a situated stance where the recording of their "live" behaviours is possible. But cognitive processes and motivations still have to be interpreted. In this paper, we propose an artificial maieutic approach to extract such pieces of knowledge, by helping the actors to better understand, and sometimes formulate, their own behaviours. The actors are playing their own roles in an agent-mediated simulation and interact with agents that question their behaviours. The actor's reactions and understanding are stimulated by these interactions, and this situation allows in many cases to reveal hidden knowledge. We present here the first results using two complementary works in social simulations, one in the domain of air traffic control and one in the domain of common-pool resources sharing.

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